Patient-specific models of blood flow may require an accurate geometric representation of the vascular network of interest. Current medical imaging data may be used to create a three-dimensional anatomic model with blood vessels ranging in size from 10 mm in diameter and above for the large main arteries, 2-5 mm for the large coronary arteries, 1-3 mm for large branch vessels, and less than a millimeter for small branch vessels. Constrained by limited image resolution and quality, these models may directly represent only the portion of the vascular network that may be observable in the image. The vessels that may be resolved may contain side branches that may be just below the limits of the image resolution and which may not be directly extracted from the data. The inclusion and/or exclusion of these branches and their downstream vascular networks may significantly influence the computed hemodynamic quantities in the observable anatomy. For example, in the coronary arterial tree where bifurcations are largely asymmetrical, arteries with cross-sectional dimensions near the limits of image resolution may be likely to give rise to small unseen side branches. Another possible scenario may be that the main vessel paths may be modeled but one or more side branches may not be included due to low image quality, image resolution, operator neglect, or lack of detection or inclusion by one or more automated image processing algorithms. In either case, the reconstructed geometry may contain long, unbranched vessel segments, which may result in artificial pressure gradients even when the vessels are free of disease. Alternatively or additionally, the unresolved vessels may be collateral vessels that may serve to bypass a region of disease and the modeled pressure loss across the diseased region may be larger than in reality due to a failure to include these vessels. Misinterpretation of these phenomena may potentially trigger a misleading diagnosis.
Therefore, there is a desire for a system and method that may 1) estimate the physical locations and geometric configurations of unresolvable and/or un-modeled vascular systems and 2) enhance the accuracy of patient-specific models of blood flow with information on un-modeled vascular systems to mitigate computational artifacts in the directly modeled regions of interest.